Matches in SemOpenAlex for { <https://semopenalex.org/work/W4327780969> ?p ?o ?g. }
Showing items 1 to 74 of
74
with 100 items per page.
- W4327780969 abstract "Deep learning and neural network methods can analyze and predict various information performance generated by financial markets. This kind of economic and financial analysis can predict and describe the trend, price, risk and other information of financial markets in a more detailed way. In order to solve the shortcomings of the existing economic and financial data analysis and research, this paper discusses the time series model function equation, convolutional neural network and economic and financial data analysis methods, and briefly discusses the test environment, data collection and indicators of the system designed in this paper. In addition, the functions of economic and financial data analysis system are designed and discussed. Finally, deep learning and neural network CNN, LSTM and RNN technologies are applied to the prediction and analysis of stock opening price, closing price, highest price and lowest price for experiments. The experimental data show that the average prediction accuracy of CNN for stock prices reaches 87.33%. The average accuracy of LSTM for stock price prediction reached 87.37%. The average prediction accuracy of RNN for stock prices reaches 97.36, which verifies that the algorithm in this paper has a good performance effect." @default.
- W4327780969 created "2023-03-19" @default.
- W4327780969 creator A5005637567 @default.
- W4327780969 date "2022-12-28" @default.
- W4327780969 modified "2023-09-26" @default.
- W4327780969 title "Economic and Financial Data Analysis System Based on Deep Learning and Neural Network Algorithm" @default.
- W4327780969 cites W2742533424 @default.
- W4327780969 cites W2809504643 @default.
- W4327780969 cites W2889295305 @default.
- W4327780969 cites W2903315783 @default.
- W4327780969 cites W2970069401 @default.
- W4327780969 cites W3024601498 @default.
- W4327780969 cites W3153842882 @default.
- W4327780969 cites W3160967379 @default.
- W4327780969 doi "https://doi.org/10.1109/ickecs56523.2022.10060240" @default.
- W4327780969 hasPublicationYear "2022" @default.
- W4327780969 type Work @default.
- W4327780969 citedByCount "0" @default.
- W4327780969 crossrefType "proceedings-article" @default.
- W4327780969 hasAuthorship W4327780969A5005637567 @default.
- W4327780969 hasConcept C10138342 @default.
- W4327780969 hasConcept C105795698 @default.
- W4327780969 hasConcept C108583219 @default.
- W4327780969 hasConcept C11413529 @default.
- W4327780969 hasConcept C119857082 @default.
- W4327780969 hasConcept C127413603 @default.
- W4327780969 hasConcept C147168706 @default.
- W4327780969 hasConcept C149782125 @default.
- W4327780969 hasConcept C151406439 @default.
- W4327780969 hasConcept C154945302 @default.
- W4327780969 hasConcept C162324750 @default.
- W4327780969 hasConcept C163068380 @default.
- W4327780969 hasConcept C204036174 @default.
- W4327780969 hasConcept C27591710 @default.
- W4327780969 hasConcept C33923547 @default.
- W4327780969 hasConcept C41008148 @default.
- W4327780969 hasConcept C50644808 @default.
- W4327780969 hasConcept C78519656 @default.
- W4327780969 hasConcept C81363708 @default.
- W4327780969 hasConceptScore W4327780969C10138342 @default.
- W4327780969 hasConceptScore W4327780969C105795698 @default.
- W4327780969 hasConceptScore W4327780969C108583219 @default.
- W4327780969 hasConceptScore W4327780969C11413529 @default.
- W4327780969 hasConceptScore W4327780969C119857082 @default.
- W4327780969 hasConceptScore W4327780969C127413603 @default.
- W4327780969 hasConceptScore W4327780969C147168706 @default.
- W4327780969 hasConceptScore W4327780969C149782125 @default.
- W4327780969 hasConceptScore W4327780969C151406439 @default.
- W4327780969 hasConceptScore W4327780969C154945302 @default.
- W4327780969 hasConceptScore W4327780969C162324750 @default.
- W4327780969 hasConceptScore W4327780969C163068380 @default.
- W4327780969 hasConceptScore W4327780969C204036174 @default.
- W4327780969 hasConceptScore W4327780969C27591710 @default.
- W4327780969 hasConceptScore W4327780969C33923547 @default.
- W4327780969 hasConceptScore W4327780969C41008148 @default.
- W4327780969 hasConceptScore W4327780969C50644808 @default.
- W4327780969 hasConceptScore W4327780969C78519656 @default.
- W4327780969 hasConceptScore W4327780969C81363708 @default.
- W4327780969 hasLocation W43277809691 @default.
- W4327780969 hasOpenAccess W4327780969 @default.
- W4327780969 hasPrimaryLocation W43277809691 @default.
- W4327780969 hasRelatedWork W2337926734 @default.
- W4327780969 hasRelatedWork W2793022090 @default.
- W4327780969 hasRelatedWork W2919358988 @default.
- W4327780969 hasRelatedWork W2963958939 @default.
- W4327780969 hasRelatedWork W3173182854 @default.
- W4327780969 hasRelatedWork W4298168912 @default.
- W4327780969 hasRelatedWork W4309045103 @default.
- W4327780969 hasRelatedWork W4311257506 @default.
- W4327780969 hasRelatedWork W4320802194 @default.
- W4327780969 hasRelatedWork W4366224123 @default.
- W4327780969 isParatext "false" @default.
- W4327780969 isRetracted "false" @default.
- W4327780969 workType "article" @default.